[1]陶倩,马刚,史忠植.基于Agent的专家系统推理模型[J].智能系统学报,2013,8(2):135-142.[doi:10.3969/j.issn.1673-4785.201210043]
TAO Qian,MA Gang,SHI Zhongzhi.Research on the expert system reasoning model based on Agent[J].CAAI Transactions on Intelligent Systems,2013,8(2):135-142.[doi:10.3969/j.issn.1673-4785.201210043]
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TAO Qian,MA Gang,SHI Zhongzhi.Research on the expert system reasoning model based on Agent[J].CAAI Transactions on Intelligent Systems,2013,8(2):135-142.[doi:10.3969/j.issn.1673-4785.201210043]
基于Agent的专家系统推理模型
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
8
期数:
2013年第2期
页码:
135-142
栏目:
学术论文—知识工程
出版日期:
2013-04-25
- Title:
- Research on the expert system reasoning model based on Agent
- 文章编号:
- 1673-4785(2013)02-0135-08
- Keywords:
- Agent; reasoning model; expert system; sporting events
- 分类号:
- TP391.6
- 文献标志码:
- A
- 摘要:
- 针对传统专家系统推理模型结构在知识获取方面适应性差的现状，从系统科学的视角，运用复杂适应系统理论，对传统专家系统的结构及运行机制进行了改进.引入Agent来模拟人脑中的神经元，用来承载专家系统中相互作用的知识，然后，基于Multi-Agent之间的相互作用来构建复杂适应的专家系统推理模型.从而，将专家系统中的知识获取机制、知识库、推理机三者统一于由Multi-Agent进行相互作用的复杂适应系统之中.通过设计体育赛事申办决策专家系统的原型，进行了专家系统推理模型的验证.原型运行结果表明：基于Multi-Agent的专家系统推理模型结构能够有效地提高专家系统知识获取的适应性.这为研究更加接近人脑智能的专家系统提供了崭新的研究思路.
- Abstract:
- The traditional expert system reasoning model structure has poor adaptability in acquiring knowledge. From the viewpoint of system science, the complex adaptive system theory is used to improve the structure and operation mechanism of a traditional expert system. Firstly, an Agent was introduced to simulate neurons in the human brain and load the knowledge interacting in the expert system reasoning model. Then an expert system reasoning model of complex adaptation was constructed based on the Multi-Agent interaction. Consequently, the knowledge acquiring mechanism, knowledge base and reasoning engine were unified into the Agents interaction in the complex adaptive expert system. Finally, by designing the expert system reasoning model prototype in decision-making of international sporting events bidding, the effectiveness of the expert system reasoning model based on Agent was verified. The results of the prototype running show that the expert system reasoning structure based on Multi-Agent model can effectively improve the adaptability of expert system knowledge acquisition. That provides a new idea for studying the expert system closer to human intelligence.
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备注/Memo
收稿日期：2012-10-21.
网络出版日期：2013-04-09.
基金项目：国家“973”计划资助项目（2013CB329502）；国家“863”计划资助项目（2012AA011003）；国家自然科学基金资助项目(61035003, 61202212, 60933004)；国家科技支撑计划资助项目（2012BA107B02）.
通信作者：陶倩.
E-mail: taoqian_101010@163.com.
作者简介：
陶倩，女，1966年生，副教授，主要研究方向为复杂适应系统建模、智能信息处理.曾主持和参与省部级科研项目，以及横向课题项目多项.发表学术论文多篇，其中2篇被EI检索.
马刚，男，1986年生，硕士研究生，主要研究方向为机器学习、数据挖掘、神经计算.曾参与国家“973”项目子课题、国家自然科学基金项目以及其他横向课题的研究，完成了多个基于多智能体专家系统的研发工作.
史忠植，男，1941年生，研究员，博士生导师.主要研究方向为智能科学、人工智能、机器学习、知识工程等．1979年、1998年、2001年均获中国科学院科技进步二等奖，1994年获中国科学院科技进步特等奖，2002年获国家科技进步二等奖．发表学术论文400余篇，出版专著15部．
更新日期/Last Update:
2013-05-26